Technical Analysis Tested on Long-run DJIA Data
March 7, 2008 - Technical Trading
Does technical analysis work after accounting for luck and trading frictions? More specifically, can traders reliably identify technical rules that generate future net outperformance? In the January 2008 version of their paper entitled “Technical Trading Revisited: Persistence Tests, Transaction Costs, and False Discoveries”, Pierre Bajgrowicz and Olivier Scaillet investigate the economic value of technical trading rules applied to long-run daily Dow Jones Industrial Average (DJIA) data. Their approach includes: (1) a new measure of data snooping bias to distinguish between luck and true forecasting power in backtesting; (2) out-of-sample persistence testing of recently successful trading rules; (3) determination of whether certain trading rules work consistently under specific economic conditions; and, (4) incorporation of trading costs. Using daily DJIA price and volume data for January 1897 through July 2007 to test 7,846 rules (filters, moving averages, support and resistance, channel breakouts and on-balance volume averages), they conclude that: Keep Reading